1. Field of the Invention
The present invention relates to image processing techniques. More specifically, the present invention relates to techniques for suppressing noise in synthetic aperture radar (SAR) imagery.
While the present invention is described herein with reference to illustrative embodiments for particular applications, it should be understood that the invention is not limited thereto. Those having ordinary skill in the art and access to the teachings provided herein will recognize additional modifications, applications, and embodiments within the scope thereof and additional fields in which the present invention would be of significant utility.
2. Description of the Related Art
Numerous technologies are currently employed to produce images from signals received by electromagnetic, electro-optical, and other sensors. Images are constructed from discrete sensor samples which are susceptible to noise. Accordingly, quality of the constructed image is often adversely affected. Noise has the effect of impeding the recognition of features by interpreters having little experience or expertise.
Prior attempts to improve the noise quality of the image have typically involved a filtering of the image data or the formation of multiple images and the performance of noncoherent integration. Each approach has certain shortcomings. In digital filtering algorithms, for example, each pixel in the image is replaced by a value which represents the average of the values of neighboring pixels. While such techniques have heretofore been somewhat effective in reducing noise, such improvement has typically come at the expense of the resolution of the image. That is, filters have been found to diminish the edge information necessary to produce sharp images. As a result, edges in filtered images tend to appear smooth.
The formation of multiple images and the performance of noncoherent integration tends to slow the operation of the system and may adversely affect system timelines.
Accordingly, there is an ongoing need in the art for techniques for suppressing noise in sensor generated images which do not require a sacrifice in image resolution. There is a particular need in the art to reduce speckle noise associated with the generation of SAR images. (Speckle noise is noise which appears as speckles in an output image.)
In "Geometric Filter for Speckle Reduction", by Thomas R. Crimmins, Applied Optics. Vol. 24, pages 1438-1443, May 15, 1985, a nonlinear algorithm is disclosed for reduction of speckle noise in SAR imagery. There are several apparent shortcomings with the Crimmins algorithm.
A first shortcoming derives from the fact that the algorithm is an iterative technique. The number of iterations required to achieve the desired performance is not known until the results are observed.
A second shortcoming derives from the fact that the Crimmins technique is nonlinear. Prediction of the performance of such nonlinear filters is problematic and the results are not necessarily reliable or repeatable when the image is changed slightly.
A third shortcoming derives from the fact that the Crimmins technique does not appear to preserve edge or other target data. Rather, it works by reducing speckle noise faster than it corrupts target data, see page 1442.
Finally, the Crimmins technique does not appear to be readily adaptable to other situations.
Thus, there is a further need in the art for an improved noniterative, content adaptive, linear speckle noise reduction technique that preserves edge or other target data and which is readily adaptable to diverse situations.